All,
Thanks so much for your comments! You have given me a lot to think about!
I am really interested in coming up with a way to reasonably assess the effectiveness of a factor to a ranking system, and just as importantly, how well or poorly that factor interacts with other factors. For example, the authors of the book Quantitative Momentum wrote an earlier book titled Quantitative Value. In the QM book, they recommended using both approaches, but not together. Instead, they recommended half of the investment pot go into QV type stocks and the other half go into QM type stocks. The reason is that (according to the authors) value and momentum are negatively correlated. The combination (in separate portfolios) tends to have more even combined returns. But the value selection combined with momentum selection into one ranking system tends to end up with lousy value stocks with lousy momentum. I like to think of value and momentum as 2 lights, or maybe like the interference patterns resulting from double slits, where value and momentum become destructive when added together, akin to the dark areas in this picture:
I used the momentum ranking system because the QM book mentioned 3 items to improve the momentum ranking that I wanted to explore: (1) the “frog in the pan” component, (2) Standardized Unexpected Earnings (SUE), and (3) Cumulative Three day abnormal returns (CAR3). I was surprised and pleased to see someone else mention SUE (see Standardized Unexpected Earnings (SUE)) and that P123 decided to provide that factor, as well as providing Standardized Unexpected Sales (SAS).
I started with the “frog in the pan” component more as a learning exercise than anything. My biggest fear was that the “frog in the pan” component (or more likely, my implementation of it) would be like the double slit experiment and that the component would have destructive contributions, either with all of the other components, or maybe with one of the other 4 components. My biggest question was this: how would I know this? If the “frog in the pan” component alone turned out to have the worst contribution factor for all stock universes, then that would be a strong clue, i.e., “This factor is not only useless, but worse than useless!” But what about the case of it interfering with another factor, e.g., quarterly returns? How would I know this?
So thanks again to everyone. I have an idea on how to proceed, and your responses have given me much to consider.
Cary